SHAPE: A Sample-Adaptive Hierarchical Prediction Network for Medication Recommendation-Reference-Cited by-同舟云学术

SHAPE: A Sample-Adaptive Hierarchical Prediction Network for Medication Recommendation

Published:2023-12 Issue:12 Volume:27 Page:6018-6028
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Liu Sicen¹^ORCID,Wang Xiaolong¹^ORCID,Du Jingcheng²^ORCID,Hou Yongshuai³^ORCID,Zhao Xianbing¹^ORCID,Xu Hui⁴,Wang Hui⁴,Xiang Yang³^ORCID,Tang Buzhou¹^ORCID

Affiliation:

1. Department of Computer Science, Harbin Institute of Technology (Shenzhen), Shenzhen, China

2. Melax Tech, Inc., Houston, TX, USA

3. Peng Cheng Laboratory, Shenzhen, China

4. Gennlife (Beijing) Technology Company, Ltd., Beijing, China

Funder

National Natural Science Foundation of China

Science and Technology Planning Project of Shenzhen Municipality

National Key R&D Program of China

Major Key Project of PCL

Strategic Emerging Industry Development Special Fund of Shenzhen

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/10345388/10266699.pdf?arnumber=10266699

Reference43 articles.

1. Scalable and accurate deep learning with electronic health records

2. A guide to deep learning in healthcare

3. A General Framework for Diagnosis Prediction via Incorporating Medical Code Descriptions

4. Using recurrent neural network models for early detection of heart failure onset

5. A hybrid method of recurrent neural network and graph neural network for next-period prescription prediction

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